Strong temporal dynamics of QTL action on plant growth progression revealed through high‐throughput phenotyping in canola

Abstract

SummaryA major challenge of plant biology is to unravel the genetic basis of complex traits. We took advantage of recent technical advances in high‐throughput phenotyping in conjunction with genome‐wide association studies to elucidate genotype–phenotype relationships at high temporal resolution. A diverse Brassica napus population from a commercial breeding programme was analysed by automated non‐invasive phenotyping. Time‐resolved data for early growth‐related traits, including estimated biovolume, projected leaf area, early plant height and colour uniformity, were established and complemented by fresh and dry weight biomass. Genome‐wide SNP array data provided the framework for genome‐wide association analyses. Using time point data and relative growth rates, multiple robust main effect marker–trait associations for biomass and related traits were detected. Candidate genes involved in meristem development, cell wall modification and transcriptional regulation were detected. Our results demonstrate that early plant growth is a highly complex trait governed by several medium and many small effect loci, most of which act only during short phases. These observations highlight the importance of taking the temporal patterns of QTL/allele actions into account and emphasize the need for detailed time‐resolved analyses to effectively unravel the complex and stage‐specific contributions of genes affecting growth processes that operate at different developmental phases.

Dissecting new genetic components of salinity tolerance in two-row spring barley at the vegetative and reproductive stages

“…[ 73 ] were unable to find overlapping QTL when studying barley during the germination and seedling stages, arguing that different tolerance mechanisms could be involved in the different stages. QTL that contribute to a certain trait can have a transient nature and dynamically change with time and developmental stages [ 54 , 74 , 75 ].…”

“…In the end, the paper was focused on QTL associated with transpiration efficiency [24]. Similarly, Peirone et al [77] found that transpiration efficiency measured in greenhouse conditions at the early stages of soybean growth was the most efficient trait in predicting drought tolerance in the field and Knoch et al [75] showed that early plant growth of canola was a complex trait that involves several temporally dynamic loci with medium and small effects. Furthermore, the heritabilities of TPA-measured traits were relatively low in our experiments, ranging between 0.5 and 0.6 (S6 Table), and these values were based on spatially adjusted means.…”

Genome-Wide Association Study (GWAS) Analysis of Camelina Seedling Germination under Salt Stress Condition

“…In order to effectively control false positives and reduce false negatives, the method iteratively performs marker tests with pseudo-quantitative trait nucleotides (QTNs) as covariates in a fixed-effect model and keeps optimizing pseudo-QTNs in a random-effect model until no new pseudo QTNs are added [34]. The capability of removing confounding effects between testing markers and kinship, preventing model overfitting and controlling false positives enable FarmCPU, has become one of the most efficient methods in current GWAS [36]. In this study, best linear unbiased predictions (BLUPs) of six seedling germination traits collected from the 211 C. sativa accessions and 6192 numerically SNPs [26] were used to perform FarmCPU algorithm in R studio.…”

“…nlm.nih.gov/genome/gdv/browser/?context=genome&acc=GCF_000633955.1) provided by Agriculture and AgriFood Canada. The LD blocks harboring significant trait-associated markers and their flanking markers with strong LD (r 2 > 0.6) were defined as candidate gene regions as suggested by Knoch et al [36]. All genes within the LD blocks were considered for candidate genes and annotated for predictive functions using C. sativa genome annotation database incorporated in snpEff [37].…”

Conventional and Molecular Techniques from Simple Breeding to Speed Breeding in Crop Plants: Recent Advances and Future Outlook

“…Currently, researchers are also using molecular genetic mapping of QTL of many complex traits vital in plant breeding. The detection and molecular cloning of genes underlying QTL enable the investigation of naturally occurring allelic variations for specific complex traits [85,153]. Plant productivity can be improved by identifying novel alleles through functional genomics or haplotype analysis.…”